Investigation of the impacts of climate change and rising temperature on food poisoning cases in Malaysia

This study is an attempt to investigate climate-induced increases in morbidity rates of food poisoning cases. Monthly food poisoning cases, average monthly meteorological data, and population data from 2004 to 2014 were obtained from the Malaysian Ministry of Health, Malaysian Meteorological Department, and Department of Statistics Malaysia, respectively. Poisson generalised linear models were developed to assess the association between climatic parameters and the number of reported food poisoning cases. The findings revealed that the food poisoning incidence in Malaysia during the 11 years study period was 561 cases per 100 000 population for the whole country. Among the cases, females and the ethnic Malays most frequently experienced food poisoning with incidence rates of 313 cases per 100,000 and 438 cases per 100,000 population over the period of 11 years, respectively. Most of the cases occurred within the active age of 13 to 35 years old. Temperature gave a significant impact on the incidence of food poisoning cases in Selangor (95% CI: 1.033–1.479; p = 0.020), Melaka (95% CI: 1.046–2.080; p = 0.027), Kelantan (95% CI: 1.129–1.958; p = 0.005), and Sabah (95% CI: 1.127–2.690; p = 0.012) while rainfall was a protective factor in Terengganu (95% CI: 0.996–0.999; p = 0.034) at lag 0 month. For a 1.0°C increase in temperature, the excess risk of food poisoning in each state can increase up to 74.1%, whereas for every 50 mm increase in rainfall, the risk of getting food poisoning decreased by almost 10%. The study concludes that climate does affect the distribution of food poisoning cases in Selangor, Melaka, Kelantan, Sabah, and Terengganu. Food poisoning cases in other states are not directly associated with temperature but related to monthly trends and seasonality.

2) Prof Budi Haryanto from Indonesia, bharyanto@ui.ac.id 3)Associate Prof Dr Rozita Hod, rozita.hod@ppukm.ukm.edu.myfrom Malaysia This statement is required for submission and will appear in the published article if the submission is accepted.Please make sure it is accurate.

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Consult the submission guidelines for detailed instructions.Make sure that all information entered here is included in the Methods section of the manuscript.Based on the Representative Concentration Pathways (RCPs) emissions, the scenarios indicated that the minimum increase of global mean surface temperature is likely to be from 0.3 °C to 1.7 °C under RCP 2.6, while the maximum increase is likely to be from 2.6 °C to

Methodology Study population
The study included the Malaysian population, irrespective of race, in all 13 states, including Sabah and Sarawak.The total population in Malaysia in 2014 was 30.72 million.Native Malays or Bumiputera recorded the highest number with 18.87 million (61.4%), followed by Chinese and Indians with 6.59 million (21.5%) and 1.98 million (6.4%), respectively.Non-Malaysians were at 3.01 million (9.8%) while others were 0.27 million (0.9%) (DOSM, 2016).

Food poisoning data, population data, and climate data
In order to explore the relationship between climate and food poisoning cases in Malaysia, the monthly data of food poisoning cases were collected from The mean and maximum data for incidence of food poisoning, temperature and rainfall for the whole Malaysia were mapped using QGIS version 3.4 long-term release.The incidence of food poisoning used choropleth maps while rainfall used the inverse distance weighing (IDW) interpolation method.The classification used the quartile method from Q1 (the lowest) to Q4 (the highest).

Model Development
Poisson generalized linear models and overdispersed Poisson models estimating the understated standard errors were run to investigate the association between climate parameters and food poisoning incidence at lag 0 month and lag 1 month.The model equation for overdispersed Poisson was the same as that for Poisson regression.The overdispersion parameter did not affect the expected outcome, but it affected the estimated variance of the expected counts.Scale weight was used to control for overdispersion by dividing the deviance to 1. Fourier terms and time stratified model were included in the model to control for seasonality and the monthly trends, respectively.Seasonality refers to the presence of variations that occur at regular monthly intervals due to the weather factor.Trend refers to the direction of data that is either increasing or decreasing, and linear assumption was used in this research.The analysis was considered towards pooled health impacts for the community at the state level.As the population increased over time, the population was set up as an offset.
The framework models were explained in Hassan et al. (2020) and El-fadel et al.
(2012).The framework was accommodated as expressed in Equation ( 1) to (3): Where ui is the exposed population at that time; λi is the expected number of cases as a fraction of the exposed population; Xi is the regression matrix; and β is the vector of model coefficients.
The robustness of the model depends on the goodness of fit.The smallest deviance, Pearson Chi Square, and Akaike information criterion (AIC) were chosen as the best model.
Sensitivity testing was conducted to determine the sensitivity of significant independent variables such as temperature and rainfall in affecting food poisoning incidences.We used lag temperature or rainfall data to replace the climate variables (temperature or rainfall) at the Lag 0 data due to the unavailability of minimum and maximum climate data in this research.If the analysis is to ensure consistency of temperature in affecting food poisoning incidences, the lag rainfall data will be used and vice versa.Similar findings with the real model indicated the model was robust.

Food poisoning cases in Malaysia
Table 1 and 2 present the demographic information and annual incidence rate for food poisoning in Malaysia.The annual incidence rate by states ranged from 2.8 to 172.3 cases per 100,000 population while the total incidence proportion of food poisoning for the whole country in Malaysia during the 11-year study period was 561 cases per 100, 000 population.
Generally, females and the ethnic Malays most frequently experienced food poisoning with incidence proportion of 313 cases per 100, 000 and 438 cases per 100,000 population over the period of 11 years, respectively.Most of the cases occurred within the active age of 13 to 35 years old.There were some missing data in the demographic information such as race and age.
However, the data was not discarded as the main outcome in this research is the total number of population cases per month instead of individual information.
Large variations were found between the minimum, mean, and maximum incidence rates in each state as shown in Figure 1 and 2. Region-wise comparative data showed that the highest annual incidence rate was recorded in Perlis state, while the minimum annual incidence rate was in Selangor state with the incidence rate of 172 cases per 100,000 population and 3 cases per 100,000 population, respectively.High incidence rate refers to the incidence rate above the 75 th percentile, while low incidence rate refers to the incidence rate below the 25 th percentile.Kelantan and Terengganu states were among the consistently highest incidence rates with the mean annual incidence rate of above 90 cases per 100,000 population.In the southern and central areas of Malaysia, Melaka consistently reported high incidence rates throughout the study period with more than 60 cases per 100,000 population.In the northern region, the incidence rates were high in Penang, Perak, and Perlis with more than 40 cases per 100,000 population.Most of the cases were recorded during the warmer months from April to August.
However, states in the northern regions such as Kedah, Penang, Perak, and Perlis, had different trends compared to other states where there were two peak periods which were at the beginning of the year in January and February, and from September and October.The peak periods were at the end of the northeast monsoon and early intermonsoon in Malaysia, respectively.All the states in Malaysia recorded the least food poisoning incidence rates during the northeast monsoon months in November and December.

Climate variations in Malaysia
Data for the 11-year study period showed that the mean monthly temperature ranged from 24.7 °C to 30.0 °C (Figure 3).The data showed very small temperature variations as Malaysia only has southwest monsoon, northeast monsoon, and inter-monsoon between these two seasons.The maximum values of the mean monthly temperature attained from April to June coinciding with the inter-monsoon and southwest monsoon period with 50.0% of the recorded temperatures were 29.0 °C and above while the minimum values occurred in December or January in conjunction with the northeast monsoon period with 60% of the temperatures being below 25.0 °C (Table 2 and Figure 4).The trend test showed an upward trend of mean monthly temperature for almost all states from 2004-2014.However, the mean monthly temperature increases were small, below 0.5 °C in 2010-2014 compared to 2004-2009 (p>0.05).
The rainfall data varied during the study period (Figure 5-6).The mean monthly rainfall and the maximum monthly rainfall for all states were between 150mm/month and 300mm/month, and 350mm/month and 1250mm/month, respectively.High rainfall was recorded during the intermonsoon (October), and northeast monsoon, except for the northern region, whereby the trends differ as the region received high rainfall in March, and August to December.The East Coast areas of Malaysia had rainfall of more than 1000mm/month in November and December.Low rainfall was recorded at the end of the northeast monsoon and southwest monsoon for all states.The months which contributed the high rainfall tally with those months with low temperature as the data showed that temperature and rainfall were inversely correlated for almost all states (r= −0.713 to −0.296).The trend test showed an upward trend of rainfall for most states in 2004-2014 although the inter-annual changes were found to be insignificant (p>0.05).

Association between climate and food poisoning incidence
Exploratory data analysis revealed a high level of multicollinearity between rainfall and relative humidity.As such, only one of these two factors can be used to ensure model stability.
Due to limited information on relative humidity research related to food poisoning compared to rainfall and the abundant rainfall in Malaysia especially during the Northeast monsoon, relative humidity was excluded from the analysis.
The Poisson GLMs and overdispersed Poisson analyses were run for all states and the results showed that temperature was significantly related to food poisoning incidences in Selangor (p=0.020),Kelantan (p=0.005),Melaka (p=0.027), and Sabah (p=0.012) at lag 0 (Table 3 and Figure 7 to 10), and Kelantan (p=0.030) at lag 1 month, while rainfall was significantly related to food poisoning incidences in Terengganu at lag 0 (p=0.034)(Figure 11).
All food poisoning incidences in other states were associated only with seasonality and/or trend.The seasonality indicated that food poisoning rates were elevated mostly during the southwest monsoon and decreased during the northeast monsoon.The overall trend of food poisoning incidences for all states were slightly decreased over the 11 years of study period except for Negeri Sembilan and Perlis.For every 1.0 °C increase in temperature, the excess risks of food poisoning in all states increased between 23.6% and 74.1%.The temperature was also tested at every increase of 0.25 °C, 0.5 °C and 0.75 °C.The results showed an upward increment of excess risks of food poisoning as the temperature increases (Table 4).Rainfall was a protective factor in Terengganu.For every 1mm increase in rainfall, the risk of getting food poisoning was decreased by less than 1%.Besides 1mm, rainfall was also tested for every increase of 10mm and 50mm and the results showed, the risk can be decreased by almost 10% if the amount of rainfall was increased.The results were consistent with Table 2 as it indicated the high incidence of food poisoning occurred during the southwest monsoon (warmer months) and low incidence in the northeast monsoon (rainy seasons).The deviance after controlling for over-dispersion was 1, and the Akaike's Information Criterion (AIC) was below 150 for all states.The final models were tested for sensitivity analysis, and the results indicated that the temperature and rainfall factors were still significant in Selangor, Kelantan, Melaka and Sabah, even if one of the independent variables was replaced.The total food poisoning annual incidences in all states in Malaysia fluctuated and ranged from 3 to 172.0 cases per 100,000 population.The variations in the incidences were large, which is due to the denominator difference.Although Selangor was reported as the state with the highest food poisoning cases, the total population in Selangor was the highest in Malaysia, therefore lowering the total incidence cases.The highest annual and monthly incidences were reported in the East Coast states such as Terengganu and Kelantan as it can reach up to 53.0 cases per 100,000 population in a month.Smaller states like Perlis and Melaka also indicated higher incidences due to low population number.

Discussion
Although all states were affected, only states that have a significant relationship with the climate: Selangor, Kelantan, Melaka, Sabah, and Terengganu, were explained in detail.
Temperature alone gave a total percentage of more than 10.0% variation for food poisoning cases in Malaysia.The increase of 1°C of temperature is associated with an excess risk of food poisoning in each state of between 23.6% to 74.1%, and 34.6% for Lag 0 and Lag 1 month, respectively.The risk of getting food poisoning was increased as the temperature increases, as presented in Table 5. Temperature in Kelantan was the only significant variable associated with an increased risk of food poisoning at Lag 1.This situation might be due to the acute effects and a short incubation period of food poisoning, and therefore, all other states showed insignificant findings.Most research showed lower excess risks compared to this research as the increase of 1.0 °C of temperature led to the percentage change of food poisoning cases of between 3.0% to 18.0% (Cullen, 2009 Terengganu is one of the east coast states that receives abundant rainfall every year during the northeast monsoon season (November-December).During rainy days, people tend to stay at home and cook their own food.The food is usually consumed while it is still hot, therefore lessens the risk of getting food poisoning as there is control of the bacterial growth.In addition, rainfall could also protect the communities against exposure to contaminated recreational water bodies.All other states showed insignificant results which may be due to the monthly mean rainfall that were low in other areas.Rainfall is usually related to floods, and floods are very common in Malaysia.However, based on a literature search conducted, very limited cases of food poisoning were reported during flood events in Malaysia.).This research received financial assistance from IRAGS18-048-0049.
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8°C under RCP 8.5 at the end of the 21 st century (IPCC 2014).In Malaysia, the observed surface temperature data had also indicated an increase in warming between 0.32 and 1.5 °C for the last five decades (MMD, 2009;Wong et al.,2018).Peninsular Malaysia indicated a higher temperature increase compared to East Malaysia, and western Peninsular Malaysia indicated the highest compared to other states (MMD, 2009).Malaysia also receives abundant rainfall annually and the East Coast areas experienced floods almost every year during the Northeast Monsoon (rainy season).With the increasing temperature, abundant rainfall during the Northeast Monsoon, and elevated food poisoning incidences, research on climatic factors influencing food poisoning incidences in hot tropical countries are essential.Previous research used Generalized linear Model (GLMs) (McIver, L et al., 2015; Hassan et al., 2020; Onozuka and Hashizume, 2011), Generalized Additive Model (GAM) (Lin et al., 2016), Quasi-Poisson regression (Zhou et al., 2013), and Pearson correlation regression(Kim, 2020) to examine the association between climate variables and infectious diseases, however GLMs are the most widely used.Therefore, this research aims to investigate the influence of climate variability on food poisoning cases in Malaysia using a Poisson generalized linear model.This research is important for future prediction of food poisoning in extreme climatic scenarios and taking into consideration the appropriate intervention measures that could be done in Malaysia.
Many papers discussed the impacts of climate change on diarrhoeal diseases in general but only limited papers were specifically on food poisoning (Bentham, & Langford 1995; D'Souza et al. 2004; El-fadel et al. 2012; Kendrovski, & Gjorgjev 2012; Kovats et al. 2004a).None of this research has been conducted in Southeast Asia, and therefore, the findings from this research will be useful as the baseline for Southeast Asia and tropical climate settings.
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IntroductionFood poisoning is defined as an acute onset of vomiting, diarrhoea, or other acute symptoms associated with the ingestion of compromised food or drinks (MOH, 2017).It can also cause the Southwest Monsoon (warmer months).These conditions increase the risk of food poisoning due to improper management in raw food supply, preparation, serving or during storage.
Monthly climate data such as relative humidity, temperature, and rainfall were obtained from MMD for the years 2004 to 2014.The missing data were estimated using the multiple regression analysis (multiple imputation method) in SPSS.The collinearity between independent variables for each state was analysed prior to model development using the correlation test and Variance Inflation Factors (VIF).Data were analysed using IBM SPSS for Windows version 23.Descriptive analysis was used to describe the demographic data, meteorological data, and morbidity data.A generalized linear model was applied for multivariate analyses.
January 2004 to December 2014 from the Ministry of Health (MOH).For demographic data, basic information such as the locality or address, age, gender, race, date of onset, and date of analysis were recorded.All incomplete dataset without medical information such as the onset date, sampling date, and diagnosis date were rejected.All these food poisoning cases were converted to incidence data by dividing it with the population data obtained from the Department of Statistics Malaysia (DOSM).
Due to limited research specifically on the role of climatic variations on food poisoning, this research uses diarrhoeal research as the comparison.Zhou et al. (2013) and Chou et al. (2010) indicated a higher excess risk of getting food poisoning of 80.0% and between 20.0% to 52.0% depending on the age groups, respectively.Different studies recorded different excess risks and relative risks due to differences in terms of geographical area, climate variability, interpretation of enteric infections, method of analysis, and varying levels of temperature increase as some studies used an increase of 1.0, 2.0, and 5.0 °C (El fadel et al., 2012; Chou et al., 2010; Ghazani et al., 2018; Zhou et al., 2013).The research also found that rainfall was only significantly related to food poisoning in Terengganu with a risk reduction of almost 10% for every 50mm increase of rainfall.Several studies supported this inverse relationship, but for diarrhoeal diseases (Beyene et al., 2019; Carlton et al., 2014; Morral et al., 2018).Comparing the thresholds with other research was difficult because every area has different climates, rainfall intensities, cut-off points, and timelags.
; El-fadel et al., 2012; Kendrovski, & Gjorgjev, 2012).Malaysia's climate is hot and humid throughout the year compared to other studies that have four seasons.Most of the food poisoning cases investigated in other studies were related to cases of Salmonellosis food poisoning, while cases in Malaysia are cumulative cases of all causes of food poisoning.Variations in geography, culture, eating behaviour and technology, food type, and hygiene are also essential factors that can trigger food poisoning for example in Malaysia, the least cases were found among Chinese due to the preference to serve food hot from the wok (Abdul Mutalib et al., 2015; Sharifa Ezat et al., 2013; Salleh et al., 2017; Zin et al., 2015; Soon et al.,2011).
(Health, 2001)(2009)reported that only 46 cases of food poisoning occurred during the major floods in Johor in December 2006 and January 2007 whereas during the major flood in 2014, there were only 27 food poisoning cases reported in Pahang(Othman, 2015), and no case was reported in Kelantan(Fauziah, 2015).Minimal cases of food poisoning during flood might be due to the complexity in specifically identifying food poisoning events from other enteric infections including gastroenteritis, or the successful public health interventions such as health education activities in the flood evacuation centres and through the media, improved sanitation and hygiene through the provision of safe water supply and toilets, and efficient management of the disposal of flood wastes and carcasses to prevent disease-breeding grounds.Between February and July every year, many events, weddings, and family gatherings are usually organized during Chinese New Year, one-week school holidays in March, and the two-week mid-term holidays in May.The increased frequency of these events may elevate the potential of getting food poisoning, especially when the food is not prepared properly (MOH, 2016; Malay Mail, 2020).During the end of the northeast monsoon and southwest monsoon seasons, Malaysia receives a minimum amount of rainfall and therefore, the temperature was high during that period.Most of the food poisoning incidences were reported during the same period.Hot weather provides an optimal temperature range for the growth of many types of toxin-producing bacteria, such as Staphylococcus aureus (37.0 °C)(Valík, 2012), Bacillus cereus (30.0 °C to 37.0 °C) (ESR, 2015), and Salmonella (35 °C to 37 °C)(Health, 2001).These temperatures are within the maximum temperature range in Malaysia.Therefore, bacterial growth and toxin production are easily induced in foods that are not served at a sufficiently high temperature.The low incidence rates of food poisoning in November and December for all states may be related to comparatively low temperature and high rainfall.The food poisoning incidences in Selangor, Melaka, Kelantan, Terengganu, and Sabah can be due to multiple factors.Selangor and Melaka received the highest temperature distributions after the northern areas.Selangor is also the most populous state in Malaysia, has a high number of squatters in pockets of the urban metropolitan area (Md.Wahid Murad et al., 2014) and has unhygienic environment and lack of basic sanitation facilities.In addition, most of the communities in these areas are working and eating outside in the restaurants.People can easily get infections through foods either during preparation, storage or serving (Abdul-Mutalib et al., 2015; Sharifa Ezat et al., 2013; Soon et al., 2011) and the temperature can accelerate the food poisoning infection in these areas.The situation in Melaka is similar to Selangor where food contaminations most possibly occurred in food premises.Food poisoning incidences in Terengganu, Kelantan and Sabah might have different possible contributing factors.Terengganu received the most abundant rainfall in Malaysia, followed by Kelantan and Pahang.However, rainfall was a protective factor for food poisoning only in Terengganu.In Kelantan and Sabah, high incidences of food poisoning were during the southwest monsoon due to hot weather.Apart from the climatic influences (temperature and rainfall), the large fraction of unexplained variance in food poisoning events observed in this area could be related to the prevalent disparity in the social factor.In conclusion, climate does affect the distribution of food poisoning cases in Selangor, Melaka, Kelantan, Sabah, and Terengganu.For a 1.0 °C increase in temperature, the excess risk of food poisoning in each state can increase up to 74.1%, whereas for every 50mm increase in rainfall, the risk of getting food poisoning is decreased by almost 10%.The excess risk is directly associated with the hot and humid climate in Selangor, Melaka, Kelantan, and Sabah, and inversely associated with rainfall in Terengganu.High rainfall in Terengganu is a protective factor towards food poisoning.Food poisoning cases in other states are not directly associated with temperature but related to seasonality and/or trends.Different states might have additional different factors that contributed to the food poisoning.Besides the climate factors, different states have other multifactorial issues such as hygiene, sanitation, low coverage of clean water supply, food contamination in the premises, and prevalent disparity in the social factor.In the future, based on the RCP model worldwide, all countries will have at least a minimum increase in temperature from 0.3 °C to 1.7 °C, and Malaysia is not excluded.It will provide an optimum temperature for a lot of pathogenic organisms.Therefore, multidisciplinary approaches are needed to control food poisoning outbreaks and improve food safety in Malaysia.Some of the measures include strengthening the management of water treatment, creating more awareness on food hygiene and sanitation, inculcating the practices of hand washing with soap, and boiling water for at least one minute to kill the microbes(EPA,        2015).It is also advised to cook food at temperatures of more than 70.0 °C to kill all the dangerous microorganisms, and store foods at the safe temperature of below 4°C.To improve food safety, several ministries should strengthen the collaborative works, for example, Ministry of Health, Department of Veterinary, and Department of Fisheries to provide certificates for the imported and exported foods, and strengthen the enforcement related to Food Act 1983.More inspection, food sampling, research activities and quality assurance programs are needed to make food safety in Malaysia successful.

Table 1
Sum of food poisoning incidences in Malaysia from 2004 to 2014.

Table 3
Correlations between meteorological factors and food poisoning at lag 0 month (model 1) and Lag 1 month (model 2)